docs: def calculate_statistics(self):
          "Jam some data through to generate statistics"
          rev_ids = range(0, 100, 1)
          feature_values = zip(rev_ids, [0] * 100)
          scores = [self.score(f) for f in feature_values]
          labels = [s['prediction'] for s in scores]
          statistics = Classification(labels, threshold_ndigits=1, decision_key='probability')
          score_labels = list(zip(scores, labels))
          statistics.fit(score_labels)
          return statistics